The power of mathematics
The power of mathematics is that it avoids all unnecessary ideas and unusual savings on thought operations. What really widens the gap between people is choice. The right choice can do more with less; the wrong choice can only do more with less. Since I have more capital, I am hopeful that it will decline and expand the spatial profit of risk-free arbitrage.
I have always believed that analysis is the backbone of applied mathematics. However, if you actually start applying the analysis to actual situations, you'll see that there's still a lot of work to be done, from grasping the general concept of an approximate method to successfully applying this method. For example, there is a problem of available time and manpower. For certain types of work, we can use sophisticated mechanical or electric devices, such as differential analyzers or electric computers. However, in most cases, we must calculate without using this method. At this point, simply knowing the convergence of the approximation process is not enough; we also have to determine which method can obtain a solution with a given degree of approximation in the shortest time, and we must make an appropriate estimate of the improved accuracy of successive approximations. All of these practical problems require us to conduct painstaking practical research. I think we really need the help of mathematicians to improve our intuitive methods, perhaps to comment and systematize our intuitive methods. In fact, successfully applying mathematics to engineering problems requires close cooperation between mathematicians and engineers. Finding the common mathematical relationships underpinning them in apparently disparate fields is no easy feat. Mathematicians who intend to conduct applied mathematics research must have a very thorough understanding of the physical processes involved. On the other hand, in order to properly use mathematical tools, engineers must thoroughly delve into the basic principles of mathematical analysis and reach a very high level. Putting together a bunch of machine tools in a disorderly manner cannot become an efficient metalworking workshop. We know there are very useful machines in your math treasure trove, and the task before us is to know how to adjust and use them.
To prove the existence of a marginal value problem, we also often use the iterative method. In other words, we do construct a series of approximate solutions. The only difference is that you only assume that the iterative process can produce a unique solution, and we've proven this. Also, in my opinion, the so-called “energy method” you use to solve problems in elastic mechanics and structural mechanics is closely related to the direct method in variability. I mean the method of directly constructing a minimization function with a given boundary value without solving the Euler-Lagrange differential equation. After all, I think there are many commonalities between pure mathematical analysis and applied mathematics.
So-called special functions. I acknowledge that mathematicians have studied many special functions, tabulated their values, and thoroughly studied their series expansions and definite integral expressions. Unfortunately, this kind of function has limited application in engineering. When exploring basic laws, physicists can select specimens with simple geometric shapes for experimental research; however, engineers have to directly handle structures with complex shapes. They cannot retreat and adopt this structure simply because the geometry of a structure is simple and the stress distribution can be calculated using a special function. Also, most special functions only work for linear problems. In the past, physicists and engineers often linearized their problems for simplicity. Mathematicians love this simplification because it makes beautiful mathematical methods useful. Unfortunately, as engineering science progresses, people need to obtain more accurate data and get closer to physical reality, which forces us to find ways to solve many nonlinear problems.
Mainly, the main players play big chess. If they want to make a big profit themselves, the less confident the other (her) people, the harder they earn. The biggest main force is The Vanguard Group, a trader with an American retirement account of 401K. In addition to Elon Musk, Tesla's largest shareholder and one of Wall Street's three major determinants.
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成熟投资者：格局，概率，取舍。没有格局必然急功近利。不计概率会把运气当技术。不懂取舍，有所不为，最后必落入陷阱和圈套。
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Elias Chen OP 74168002 : Elias=Jerome's judgment on Tesla is: short short and long long. Elias=Jerome is a strategic investor in Tesla. For Elias=Jerome, a decline is an opportunity. He has a plan and steps, divided into gradients and batches, and discrete random variables to build positions.